Taking advantage of both the scaling property of wavelets and the high learning ability of neural networks, wavelet networks have recently emerged as a powerful tool in many applications in the field of signal processing such as data compression, function approximation as well as image recognition and classification. A novel wavelet network-based method for image classification is presented in ...

Animal studies have shown that prenatal stress is able to induce long-lasting neurobiological and behavioral alterations in adult offspring. In spite of the facts that hippocampus is sensitive to early developmental influences and its known functional importance in learning and memory, few data are available on the effect of prenatal stress on the structure of hippocampus. Therefore, this study...

We propose and implement a pyramidal image blending algorithm using modern programmable graphic processing units. This algorithm is an essential part of an image stitching process for a seamless panoramic mosaic. The CUDA framework is a novel GPU programming framework from NVIDIA. We realize significant acceleration in computations of the pyramidal image blending algorithm by utilizing the CUDA...

Pyramid Image Coding is a natural coding scheme for applications where progressive transmission is desired. In this kind of coder, versions of the original image at several resolution levels are formed by successive filtering and subsampling. Then, beginning from the coarsest image, the image is used to produce an estimate for the next (higher resolution) level and the error is coded and transm...

We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains cycles. Each level of the hierarchical structure features the same number of sites as the base level and each site on a given level has several neighbors on the parent level. Compared to tree structured models, the (s...

This paper is concerned with hierarchical Markov Random Field (MRF) models and with their application to sonar image segmentation. We present a novel unsupervised hierarchical MRF model involving a pyramidal label eld and a scale-causal and spatial neighborhood structure. This allows us to more precisely model the local and global characteristics of image content for diierent scales. Such conne...

This paper presents a method for retrieval of remote sensing images using low dimensional code of the spatial layout of a scene, which is proposed to represent the meaning of the scene. This semantic feature is based on the statistical features of gradient orientations. To capture coarse spatial information, the semantic feature is represented in a pyramidal structure. The level of the pyramid ...